Identification of informative cooperator herds for progeny testing based on yield deviations.

Area of Science:

• Animal Breeding and Genetics
• Dairy Science
• Quantitative Genetics

Background:

• Cooperative herds are crucial for progeny testing in dairy breeding.
• Efficient strategies for selecting informative herds are currently lacking.
• Genetic differentiation within herds is key for accurate breeding value estimation.

Purpose of the Study:

• To evaluate a novel methodology for selecting the most informative cooperative herds for progeny testing.
• To utilize yield deviations (YD) for assessing genetic differentiation among herds.
• To provide a practical approach for optimizing dairy cattle breeding programs.

Main Methods:

• Analysis of yield deviations (YD) for protein, fat, milk yield, and somatic cell score from 717,377 first-lactation cows in Germany (2003-2008).
• Ranking and classification of daughters within sire based on YD.
• Merging daughter YD data with herd-calving year (HCY) characteristics (production level, somatic cell count, age at first calving).
• Calculation of herd ranks based on averaged YD percentages over the analyzed period.

Main Results:

• Herds with extreme YD classes showed high production, low somatic cell counts, and early age at first calving.
• Herds in the top quartile exhibited high average protein yield, high intra-herd production index variation, and low age at first calving.
• High correlations (0.64-0.86) between herd rankings for different traits and across regions/years were observed.
• Strong correlation (0.87) for protein yield between extreme herd quartiles indicated minimal genotype by environment interaction.

Conclusions:

• The proposed YD-based methodology is effective and easy to implement for identifying informative cooperative herds.
• This approach is suitable for various herd sizes, including smaller operations.
• The method supports the development of sustainable and competitive dairy cattle breeding programs by optimizing herd selection.